Interpreting medical tables as linked data for generating meta-analysis reports

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dc.contributor.authorMulwad, Varish
dc.contributor.authorFinin, Tim
dc.contributor.authorJoshi, Anupam
dc.date.accessioned2018-11-02T14:00:12Z
dc.date.available2018-11-02T14:00:12Z
dc.date.issued2014-08-15
dc.description15th IEEE Int. Conf. on Information Reuse and Integrationen_US
dc.description.abstractEvidence-based medicine is the application of current medical evidence to patient care and typically uses quantitative data from research studies. It is increasingly driven by data on the efficacy of drug dosages and the correlations between various medical factors that are assembled and integrated through meta-analyses (i.e., systematic reviews) of data in tables from publications and clinical trial studies. We describe a important component of a system to automatically produce evidence reports that performs two key functions: (i) understanding the meaning of data in medical tables and (ii) identifying and retrieving relevant tables given a input query. We present modifications to our existing framework for inferring the semantics of tables and an ontology developed to model and represent medical tables in RDF. Representing medical tables as RDF makes it easier for the automatic extraction, integration and reuse of data from multiple studies, which is essential for generating meta-analyses reports. We show how relevant tables can be identified by querying over their RDF representations and describe two evaluation experiments: one on mapping medical tables to linked data and another on identifying tables relevant to a retrieval query.en_US
dc.description.sponsorshipThis research was supported by NSF awards 1228198, 1250627 and 0910838 and a gift from Microsoft Research.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/7051955en_US
dc.format.extent10 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/M24B2X84S
dc.identifier.citationVarish Mulwad, Tim Finin and Anupam Joshi, Interpreting Medical Tables as Linked Data to Generate Meta-Analysis Reports, 15th IEEE Int. Conf. on Information Reuse and Integration, IEEE, August 2014, DOI: 10.1109/IRI.2014.7051955en_US
dc.identifier.uri10.1109/IRI.2014.7051955
dc.identifier.urihttp://hdl.handle.net/11603/11835
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rights© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.subjectHypertensionen_US
dc.subjectOntologiesen_US
dc.subjectCorrelationen_US
dc.subjectUnified modeling languageen_US
dc.subjectData miningen_US
dc.subjectSemanticsen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.subjectmedical table interpretationen_US
dc.subjectretrieval queryen_US
dc.subjectResource description frameworken_US
dc.subjectdata integrationen_US
dc.titleInterpreting medical tables as linked data for generating meta-analysis reportsen_US
dc.typeTexten_US

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